What are Stop Words?

And what are they used for?

  • \(Stop\) \(words\) are words that are frequently used in a language but are usually filtered out in text analysis because they are considered to be of little value in understanding the meaning of a sentence. These common words, like "and," "the," and "is," are often removed to focus on the more meaningful and contextually relevant terms for more effective language processing.

  • Stop words are useful in \(Natural \) \(Language \) \(Processing \) (or NLP) which is a specialized field in Machine learning devoted to interpreting human language.

Common Stop Words

English

There are several popular natural language processing (NLP) libraries and frameworks used in various programming languages. Each of these libraries has a different list of stop words. The use of different stop words in various NLP libraries is often influenced by factors such as the library's intended use case, the target audience, and the linguistic preference of its developers. 

Spanish

Every language has its own unique set of stop words. Here is a set of examples from the Spanish language that are largely filtered out because—just like in English— they offer little when it comes to understanding the meaning of a sentence. 

Around the World

In different languages, stop words contribute differently to the overall text structure:

  • English

    In general text, stop words may account for 40-50% of the total words.

  • French and Spanish

    Stop words are often slightly higher in frequency than English due to grammatical structures. They may make up 50-60% of the total vocabulary in a typical document.

  • Chinese or Japanese

    Stop word percentages are lower (around 30-40%), as these languages rely more on characters and compound words.

Programming Libraries

And Their Functions for Identifying & Removing Stop Words

Python: NLTK (Natural Language Toolkit) 

NLTK is a powerful library for natural language processing in Python. It provides a list of stop words for various languages and functions to remove them.

NLTK functions for identifying and removing stop words.

Python: spaCy

SpaCy is another popular NLP library for Python. It comes with prebuilt models for various languages and includes functionality to remove stop words. 

spaCy functions for identifying and removing stop words.

Java: Apache OpenNLP

Apache OpenNLP is a Java library for natural language processing. It provides a pre-built stop words list and functions to filter them from text. 

OpenNLP functions for identifying and removing stop words.

FAQ

  • Why do we need to remove stop words in NLP tasks?

    Removing stop words helps to reduce the dimensionality of the text data, leading to more efficient computation and allowing models to focus on the most informative words. Since stop words are often the same across different types of text, they contribute little to differentiating between different texts.

  • Are stop words always removed?

    No. In some cases, stop words carry important meaning. For example, in sentiment analysis, words like "not" or "but" can change the meaning of a sentence, so you would not want to remove them. Additionally, some modern NLP models, such as transformers, handle stop words more effectively without needing explicit removal.

  • Can I create my own stop word list?

    Yes, you can customize a stop word list based on the specific needs of your project. Many libraries (such as NLTK or spaCy) allow users to add or remove words from the default stop word list.

Text Preprocessing

Learn more about stop words, tokenization, and more!

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